This paper addresses the application of neural network research to a theory of autonomous systems Neural net works while enjoying considerable success in autonomous systems applications have failed to provide a rm the oretical underpinning to neural systems embedded in their natural ecological context This paper proposes a stochastic formulation of such an embedding A neural system derived from...

We study how total factor productivity (TFP), energy prices and the great moderation are linked. First, we estimate a joint stochastic process for the energy price and TFP and establish that until 1982:II, energy prices negatively affected productivity. This spill-over has since disappeared. Second, we show that within the framework of a Dynamic Stochastic General Equilibrium (DSGE) model, the ...

We study how total factor productivity (TFP), energy prices, and the Great Moderation are linked. First we estimate a joint stochastic process for the energy price and TFP and establish that until the second quarter of 1982, energy prices negatively affected productivity. This spillover has since disappeared. Second, we show that within the framework of a dynamic stochastic general equilibrium ...

Dynamic heterogeneity has often been modeled by assuming that a single-particle observable, fluctuating at a molecular scale, is influenced by its coupling to environmental variables fluctuating on a second, perhaps slower, time scale. Starting from the most simple Gaussian Markov process we model the exchange between 'slow' and 'fast' environments by treating the fluctuating single-particle va...

spatial-temporal modeling of air pollutants, ground-level ozone concentrations in particular, has attracted recent attention because by using spatial-temporal modeling, can analyze, interpolate or predict ozone levels at any location. in this paper we consider daily averages of troposphere ozone over tehran city. for eliminating the trend of data, a dynamic linear model is used, then some featu...

Recent research has investigated ways in which general probability distributions may be incorporated into stochastic process algebra. These proposals allow the arbitrary use of such distributions, improving expressibility, but in general this makes performance evaluation diicult. Typically, simulation techniques must be employed. We attack the goal of general probability distributions from the ...

Two different descriptions are used in the literature to formulate the optimal dynamic output feedback control problem for linear dynamical systems with white stochastic parameters and quadratic criteria, called the optimal compensation problem. One describes the matrix valued white stochastic processes involved, using a sum of deterministic matrices each one multiplied by a scalar stochastic p...

We introduce Stochastic Process Algebras as a novel approach for the structured design and analysis of both the functional behaviour and performabil-ity (i.e performance and dependability) characteristics of parallel and distributed systems. This is achieved by integrating stochastic modelling and analysis into the powerful and well investigated formal description techniques of process algebras...